Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

Array of sensors: A spatiotemporal-state-space model for target trajectory tracking

In this paper, with the objective of tracking the trajectory of multiple mobile targets, a novel spatiotemporal-state-space model is introduced for an array of sensors distributed in space. Under the wideband assumption, the proposed model incorporates the array geometry in conjunction with crucial target parameters namely (i) ranges, (ii) directions, (iii) velocities and (iv) associated Doppler effects. Computer simulation studies show some representative examples where the proposed model is utilised to track the locations of sources in space with a very high accuracy

Positioning of High-speed Trains using 5G New Radio Synchronization Signals

We study positioning of high-speed trains in 5G new radio (NR) networks by utilizing specific NR synchronization signals. The studies are based on simulations with 3GPP-specified radio channel models including path loss, shadowing and fast fading effects. The considered positioning approach exploits measurement of Time-Of-Arrival (TOA) and Angle-Of-Departure (AOD), which are estimated from beamformed NR synchronization signals. Based on the given measurements and the assumed train movement model, the train position is tracked by using an Extended Kalman Filter (EKF), which is able to handle the non-linear relationship between the TOA and AOD measurements, and the estimated train position parameters. It is shown that in the considered scenario the TOA measurements are able to achieve better accuracy compared to the AOD measurements. However, as shown by the results, the best tracking performance is achieved, when both of the measurements are considered. In this case, a very high, sub-meter, tracking accuracy can be achieved for most (>75%) of the tracking time, thus achieving the positioning accuracy requirements envisioned for the 5G NR. The pursued high-accuracy and high-availability positioning technology is considered to be in a key role in several envisioned HST use cases, such as mission-critical autonomous train systems.Comment: 6 pages, 5 figures, IEEE WCNC 2018 (Wireless Communications and Networking Conference

Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System

Background theory, a reference design, and demonstration results are given for a Global Navigation Satellite System (GNSS) interference localization system comprising a distributed radio-frequency sensor network that simultaneously locates multiple interference sources by measuring their signals’ time difference of arrival (TDOA) between pairs of nodes in the network. The end-to-end solution offered here draws from previous work in single-emitter group delay estimation, very long baseline interferometry, subspace-based estimation, radar, and passive geolocation. Synchronization and automatic localization of sensor nodes is achieved through a tightly-coupled receiver architecture that enables phase-coherent and synchronous sampling of the interference signals and so-called reference signals which carry timing and positioning information. Signal and crosscorrelation models are developed and implemented in a simulator. Multiple-emitter subspace-based TDOA estimation techniques are developed as well as emitter identification and localization algorithms. Simulator performance is compared to the CramérRao lower bound for single-emitter TDOA precision. Results are given for a test exercise in which the system accurately locates emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic